2025 ASEE Annual Conference & Exposition

Mathematical modeling is a key component of the engineering design process [1]. When students engage in modeling activities, they tackle complex problems similar to those faced by engineers in practice [2]. However, mathematics education in engineering classrooms often focuses on simple textbook problems and mechanistic processes [3], [4], leading first-year students to feel a disconnect between mathematics and engineering concepts [5]. This approach contrasts with ABET outcomes, which emphasize using mathematical principles to solve complex engineering problems [6]. Additionally, while the ABET emphasize that students develop the ability to make informed judgments in societal contexts [6], Hoople et al. [7] note that engineering courses often present problems that lack social contexts. Therefore, it is urgent to implement changes in the engineering curriculum that integrate disciplinary and societal knowledge [8].
This evidence-based work paper aims to contribute to the mathematics engineering education research by exploring the integration of learning experiences that foster the development of disciplinary knowledge in mathematics and engineering within social contexts. Our study draws on the Models and Modeling Perspective [9], which advocates for the use of Models Eliciting Activities (MEAs) -“realistic, complex problem-solving tasks that elicit documentation of students’ thinking and procedures through having students create models” [3, p. 281] -, and Appropriate Technology framework [10], which emphasizes reorienting engineering toward organic, gentle, and non-violent technologies that respect the environment, individuals and communities, particularly those marginalized. This study was guided by the research question: How does a team of first-year engineering students incorporate disciplinary and societal aspects in their solution to the Ram Pump MEA?
We selected a team of first-year engineering students at a Hispanic-Serving Institution in Southwest Texas. An MEA was designed to encourage students to select and mathematically model a pumping system to provide running water to households in underserved communities along the U.S.-Mexico border. The data for analysis came from the presentations and models the students developed to solve the MEA.
We employed Epistemic Network Analysis (ENA) to analyze students’ cognitive integration processes. “ENA is a set of techniques that identifies and measures connections among elements in coded data and represents them in dynamic networks models” [11, pp. 9–10], designed to model the structure of connections among cognitive elements. Our analysis examined the constructs of mathematical knowledge, basic fluid mechanics knowledge, and critical reflections on the decisions regarding the implementation of technologies within the social context of the MEA.
Our rigorous analysis derived from the ENA models revealed that the MEA enabled students to develop cognitive networks that reflected the integration of the three analyzed constructs. These networks connected mathematization [12] and measurement processes with concepts of efficiency and critical reflection. Our findings suggest that incorporating mathematical modeling activities into engineering courses provides students with the opportunity to move beyond mechanistic processes toward a more holistic approach. This approach integrates fundamental aspects of ABET [6] student outcomes, linking mathematical knowledge for solving complex engineering problems with the ability to recognize and make informed decisions in societal contexts.